Rui Zhou

Distributionally Robust Sequential Recommnedation

2023

Modeling user sequential behaviors have been demonstrated to be effective in promoting the recommendation performance. While previous work has achieved remarkable successes, they mostly assume that the training and testing distributions are consistent, which may …

Novel MITM attack scheme based on built-in negotiation for blockchain-based digital twins

2023 · Digital Communications and Networks

As smart contracts, represented by Solidity, become deeply integrated into the manufacturing industry, blockchain-based Digital Twins (DT) has gained momentum in recent years. Most of the blockchain infrastructures in widespread use today are based on …

Network Topology Inference with Sparsity and Laplacian Constraints

2023

We tackle the network topology inference problem by utilizing Laplacian constrained Gaussian graphical models, which recast the task as estimating a precision matrix in the form of a graph Laplacian. Recent research [1] has uncovered …

OoDIS: Anomaly Instance Segmentation and Detection Benchmark

2024 · arXiv (Cornell University)

Safe navigation of self-driving cars and robots requires a precise understanding of their environment. Training data for perception systems cannot cover the wide variety of objects that may appear during deployment. Thus, reliable identification of …

Research on contemporary Chinese Go books—based on a macro perspective

2024 · Journal of Go Studies

Go books have played an important role in the spread of Go for thousands of years. However, looking at the existing research in the academic community, there is a lack of interpretation of contemporary Chinese …

Quantum Algorithms for the Maximum K-Plex Problem

2024

The k-plex model, which allows each vertex to miss connections with up to$k$neighbors, serves as a relaxation of the clique model. Its adaptability makes it more suitable for analyzing graphs from real-world applications, where noise …

SSKD: Stepwise Self-Knowledge Distillation for Binary Neural Networks in Keyword Spotting

2026 · Applied Sciences

The hardware power-aware keyword spotting (KWS) implementation requires small memory footprint, low-complex computation, and high accuracy performances. Binary neural networks (BNNs) naturally satisfy these constraints. They quantize both weights and activations to 1-bit. This reduces …